我想在matshow中看到比例尺,我找了很长时间,没有找到答案。我怎么做?
代码很简单:
def analyze_results():
l_points = [np.array([10, 9, -1]), np.array([-4, 4, 1]), np.array([-6, 2, -1]), np.array([ 7, -2, 1]), np.array([-3, 2, -1]), np.array([ 3, -5, -1]), np.array([-5, 10, 1]), np.array([-10, 9, -1]), np.array([ 4, -4, 1]), np.array([-4, 7, 1])]
num_elemnts = 2 * const_limit + 1
loss = np.zeros((num_elemnts, num_elemnts))
for i in range(-const_limit, const_limit + 1):
for j in range(-const_limit, const_limit + 1):
if ((i == 0) & (j == 0)):
continue
w = (i, j)
loss[i, j] , …Run Code Online (Sandbox Code Playgroud) 我有一个random.choice的问题,我无法理解.我将3个参数传递给允许有4个的函数(http://docs.scipy.org/doc/numpy-1.10.0/reference/generated/numpy.random.choice.html),但它写的我是只允许给出2和4.
def load_data():
dataset = load_boston()
num_samples = size(dataset.data, 0)
test_set_sz = int(1.0 * num_samples / 10)
tst_sub_inds = random.choice(range(num_samples), test_set_sz, False)
data_test, label_test = dataset.data[tst_sub_inds, :], dataset.target[tst_sub_inds]
trn_sub_inds = list(set(range(num_samples)) - set(tst_sub_inds))
data_train, label_train = dataset.data[trn_sub_inds, :], dataset.target[trn_sub_inds]
return ((data_train, label_train), (data_test, label_test))
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错误:
tst_sub_inds = random.choice(range(num_samples),test_set_sz,False)TypeError:choice()需要2个位置参数,但4个被赋予Blockquote
问题是什么?也许是因为旧版的python?
谢谢,Eli